Contagious Sets in Expanders

Abstract: We consider the following activation process in undirected graphs: a vertex is active either if it belongs to a set of initially activated vertices or if at some point it has at least $r$ active neighbors, where $r&gt;1$ is the activation threshold. A \emph{contagious set} is a set whose activation results with the entire graph being active. Given a graph $G$, let $m(G,r)$ be the minimal size of a contagious set. Computing $m(G,r)$ is NP-hard. It is known that for every $d$-regular or nearly $d$-regular graph on $n$ vertices, $m(G,r) \le O(\frac{nr}{d})$. We consider such graphs that additionally have expansion properties, parameterized by the spectral gap and/or the girth of the graphs. The general flavor of our results is that sufficiently strong expansion (e.g., $\lambda(G)=O(\sqrt{d})$, or girth $\Omega(\log \log d)$) implies that $m(G,2) \le O(\frac{n}{d<sup>2})$ (and more generally, $m(G,r) \le O(\frac{n}{d<sup>{r/(r-1)}})$). Significantly weaker expansion properties suffice in order to imply that $m(G,2)\le O(\frac{n \log d}{d<sup>2})$. For example, we show this for graphs of girth at least~7, and for graphs with $\lambda(G)&lt;(1-\epsilon)d$, provided the graph has no 4-cycles. Nearly $d$-regular expander graphs can be obtained by considering the binomial random graph $G(n,p)$ with $p \simeq \frac{d}{n}$ and $d &gt; \log n$. For such graphs we prove that $$\Omega(\frac{n}{d² \log d}) \le m(G,2) \le O(\frac{n\log\log d}{d^2\log d})$$ almost surely. Our results are algorithmic, entailing simple and efficient algorithms for selecting contagious sets.